How can we use the $PA=LU$ decomposition to solve a system of linear equations?

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In summary, the $PA=LU$ decomposition method is a numerical technique used to efficiently solve a system of linear equations by decomposing a matrix into three simpler matrices. This method is particularly useful for solving large systems with many variables and can also be used for multiple systems with the same coefficient matrix. However, it is limited to square matrices and may not be as efficient for sparse or structured matrices. In these cases, other methods may be more suitable. Additionally, the decomposition process can be more computationally intensive for matrices with large condition numbers.
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Chris L T521
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Thanks to those who participated in last week's POTW! Here's this week's problem!

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Problem: Given the matrix $A=\begin{pmatrix}2 & 1 & 5\\ 4 & 4 & -4\\ 1 & 3 & 1\end{pmatrix}$,

(a) Find it's $PA=LU$ decomposition where $P$ is a permutation matrix, $L$ is a lower triangular matrix, and $U$ is an upper triangular matrix.
(b) Use its $PA=LU$ decomposition to solve $\begin{pmatrix}2 & 1 & 5\\ 4 & 4 & -4\\ 1 & 3 & 1\end{pmatrix} \begin{pmatrix} x_1 \\ x_2 \\ x_3 \end{pmatrix} = \begin{pmatrix} 5 \\ 0 \\ 6 \end{pmatrix}$

Hint for (b):
Solve the matrix equations $Lc=Pb$ and $Ux=c$ and then use back substitution.

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  • #2
Sorry about posting the solution late - I was studying for my analysis prelim this past week and did some more cramming last night, and in the process I forgot about updating the POTWs for this week. The exam was this morning and was much better than what I was expecting - I'll know how well I did in the next couple weeks.

Anyways, this week's problem was correctly answered by Sudharaka. His solution can be found below.

The LUP decomposition is not unique. One possible answer is,

\[\begin{pmatrix}0& 1& 0\\0& 0& 1\\1& 0& 0\end{pmatrix}\begin{pmatrix}2 & 1 & 5\\ 4 & 4 & -4\\ 1 & 3 & 1\end{pmatrix}=\begin{pmatrix}1&0&0\\ 0.25& 1& 0\\ 0.5& -0.5& 1\end{pmatrix}\begin{pmatrix} 4& 4& -4\\ 0& 2& 2\\ 0& 0& 8\end{pmatrix}\]\[\Rightarrow\begin{pmatrix}2 & 1 & 5\\ 4 & 4 & -4\\ 1 & 3 & 1\end{pmatrix}=\begin{pmatrix}0& 1& 0\\0& 0& 1\\1& 0& 0\end{pmatrix}^{-1}\begin{pmatrix}1&0&0\\ 0.25& 1& 0\\ 0.5& -0.5& 1\end{pmatrix}\begin{pmatrix} 4& 4& -4\\ 0& 2& 2\\ 0& 0& 8\end{pmatrix}\]Therefore,\[\begin{pmatrix}0& 1& 0\\0& 0& 1\\1& 0& 0\end{pmatrix}^{-1}\begin{pmatrix} a_1 \\ a_2 \\ a_3 \end{pmatrix} = \begin{pmatrix} 5 \\ 0 \\ 6 \end{pmatrix}\]\[\Rightarrow \begin{pmatrix} a_1 \\ a_2 \\ a_3 \end{pmatrix} = \begin{pmatrix}0& 1& 0\\0& 0& 1\\1& 0& 0\end{pmatrix} \begin{pmatrix} 5 \\ 0 \\ 6 \end{pmatrix}= \begin{pmatrix} 0 \\ 6 \\ 5 \end{pmatrix}\]Now, \[\begin{pmatrix}1&0&0\\ 0.25& 1& 0\\ 0.5& -0.5& 1\end{pmatrix}\begin{pmatrix} b_1\\b_2\\b_3\end{pmatrix}=\begin{pmatrix} 0 \\ 6 \\ 5 \end{pmatrix}\]\[\Rightarrow \begin{pmatrix} b_1\\b_2\\b_3\end{pmatrix}=\begin{pmatrix} 0\\6\\8\end{pmatrix}\]Again we have,\[\begin{pmatrix} 4& 4& -4\\ 0& 2& 2\\ 0& 0& 8\end{pmatrix}\begin{pmatrix} x_1\\x_2\\x_3\end{pmatrix}=\begin{pmatrix} 0 \\ 6 \\ 8 \end{pmatrix}\]\[\Rightarrow \begin{pmatrix} x_1\\x_2\\x_3\end{pmatrix}= \begin{pmatrix} -1\\2\\1\end{pmatrix}\]
 

Related to How can we use the $PA=LU$ decomposition to solve a system of linear equations?

1. What is the $PA=LU$ decomposition method?

The $PA=LU$ decomposition method is a numerical technique used to solve a system of linear equations. It decomposes a matrix into the product of a permutation matrix ($P$), a lower triangular matrix ($L$), and an upper triangular matrix ($U$). This method is often used when solving large systems of linear equations, as it can be more computationally efficient than other methods.

2. What is the benefit of using $PA=LU$ decomposition?

The main benefit of using the $PA=LU$ decomposition method is that it can reduce the computational complexity of solving a system of linear equations. By decomposing the matrix into three simpler matrices, the system can be solved using forward and backward substitution, which is less computationally intensive than other methods.

3. How does the $PA=LU$ decomposition method work?

The $PA=LU$ decomposition method works by first permuting the rows of the original matrix to create a new matrix $PA$. This permutation allows for easier decomposition into lower and upper triangular matrices. The lower triangular matrix $L$ is then created by filling in the lower portion of the matrix with the multipliers used in Gaussian elimination. The upper triangular matrix $U$ is created by filling in the upper portion of the matrix with the remaining values after performing Gaussian elimination. Finally, the system can be solved using forward and backward substitution on the decomposed matrices.

4. When should I use $PA=LU$ decomposition to solve a system of linear equations?

The $PA=LU$ decomposition method is most useful when solving large systems of linear equations, particularly those with many variables. It can also be useful when solving multiple systems with the same coefficient matrix, as the decomposition only needs to be performed once. Additionally, this method may be preferred over other methods when the matrix is not sparse and does not have any special structure.

5. What are the limitations of the $PA=LU$ decomposition method?

One limitation of the $PA=LU$ decomposition method is that it can only be used for square matrices. Additionally, the method may not be as efficient for sparse matrices or matrices with special structure, such as banded or symmetric matrices. In these cases, other methods such as Cholesky decomposition or sparse matrix techniques may be more efficient. Lastly, the decomposition process can be more computationally intensive for matrices with large condition numbers, which can lead to numerical instability.

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